How AI Can Calculate Our Oil Surplus...From Space

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How AI Can Calculate Our Oil Surplus...From Space

Orbital Insight/DigitalGlobe

No one knows how much oil we have left on the planet. No one can even say with any certainty how much oil is waiting to hit the market. The startup Orbital Insight thinks it can answer those questions by analyzing satellite photos.

Founder Jimi Crawford—an AI expert who has worked for NASA and Google—explains that it can do this by analyzing massive numbers of photos of oil tanks with floating lids. As a tank is depleted, the lid sinks, and the sun casts shadows on the inside of the tank changes. By detecting patterns in how those shadows change, analysts can estimate how much oil is available in all the tanks it monitors.

To spot these patterns, the company uses some of the same artificial intelligence techniques Facebook and Google use to analyze photos. But instead of trying to find pictures of cats, or recognize which of your drunk friends is in that photo you took at the bar last night, Orbital Insight hopes to discover information that affects the global economy, like oil surpluses or shortages.

That's one example of what could be possible with Orbital Insight's technology. Crawford says the company already is working with several hedge funds on projects such as estimating how much construction is occurring in China, how much grain was harvested last season in Russia, and how many cars are parked at big-box retailers around the world, data that could help suss out shopping trends.

But Crawford wants Orbital Insight, which just raised a $8.5 million round of financing led by Sequoia Capital, to do more than help investors make smarter bets. "We're trying to understand large-scale trends and put them together for policymakers and decision makers, including corporations and non-government organizations," he says. Governments or environmental organizations could, for example, use the technology to monitor deforestation.

Governments and corporations have been analyzing satellite imagery for years. But it's only recently that costs have reached the point where a company like Orbital Insight could acquire fresh imagery daily without going broke. That's due in large part to the rise of "nano-satellites"—relatively inexpensive satellites powered by smartphone technology. These satellites are cheaper to build and cheaper to launch because many of them can be packed onto a single rocket. Depending on the size of the satellite, they can be launched for anywhere from $300,000 to $2 million, says Jason Andrews, the CEO of Spaceflight Services, a company that makes and launches satellites, and provides satellite communications services.

These cheap satellites aren't as powerful as traditional satellites, but they're good enough to capture photos from space. "Pictures from space used to cost thousands dollars and it would take a month to get them," he says. That's why the photos you see in Google Earth aren't updated every day. But companies like SkyBox, acquired by Google last year, and Planet Labs can provide this type of imagery on a daily basis for a fraction of the cost.

The rise of nano-satellites is what inspired Crawford to start Orbital Insight. But instead of making his own satellites, he decided to focus on the software. Crawford's team is using a wide range of machine learning and computer vision techniques to automatically analyze the photos they collect from imagery companies, including deep learning, a field within artificial intelligence that companies like Facebook and Google have become obsessed with.

"At NASA the problem was that the budget got eaten up mostly by hardware," he says. "It's incredibly hard to build a world class company in both hardware and software. So we want to leave it to the hardware companies to do the hardware and be the best company in the software side."